Collection Frequency Based Data Model

1. A non-transitory computer-readable storage medium storing computer-executable instructions that when executed by a computer cause the computer to: identify a plurality of facts comprising at least a first fact and a second fact, wherein data for the first fact is to be collected at a first collection frequency that is greater than a second collection frequency at which data is to be collected for the second fact, wherein each of the plurality of facts corresponds to a given attribute of a given point type; determine the first collection frequency and the second collection frequency for the data to be collected for the plurality of facts; create data structures defining separate sample tables, the separate tables comprising a first table for storing the data collected for the first fact and a second table for storing the data collected for the second fact, where the separate sample tables record a point identifier, the data for the first fact and the second fact, and a collection time for the data; select different levels of partitioning for the separate sample tables based, at least in part, on the first collection frequency and the second collection frequency of the data for the plurality of facts; control query access to the separate sample tables that store data collected at the first collection frequency and the second collection frequency, and have the different levels of partitioning, wherein the query access is controlled by preventing performance of an ad hoc query on the first table that stores the data collected for the first fact and enabling performance of an ad hoc query on the second table that stores the data collected for the second fact; and store subsequently received data in the separate sample tables according to the different levels of partitioning selected for the separate sample tables based on the first collection frequency and the second collection frequency.

2. The non-transitory computer-readable medium of claim 1 , where the computer-executable instructions further cause the computer to deduce a valid time for the data based on at least one of the first collection frequency and the second collection frequency.

3. The non-transitory computer-readable medium of claim 1 , where the computer-executable instructions further cause the computer to: assign a unique fact identifier to each of the plurality of facts.

4. The non-transitory computer-readable medium of claim 1 , where a given point type identified by the point identifier corresponds to a relationship and the data describes the relationship for the given point type.

5. The non-transitory computer-readable medium of claim 1 , where a given point type corresponds to a status and the data describes the status of the given point type.

6. A computing system, comprising: at least one processor connected to at least one memory comprising a non-transitory computer readable medium; where the memory stores a data model configured to store data for a plurality of facts, the plurality of facts comprising at least a first fact and a second fact, where each of the plurality of facts corresponds to a given attribute of a given point type, and data for the first fact is to be collected at a first collection frequency and data for the second fact is to be collected at a second collection frequency, wherein the first collection frequency is greater than the second collection frequency; where the memory stores separate sample tables comprising a first table for the first fact and a second table for the second fact, where each of the separate sample tables records a point identifier, the data, and a collection time for the data; where the data model comprises sample table metadata that: (i) assigns different levels of partitioning to the separate sample tables, the different levels of partitioning being based, at least in part, on a difference between the first collection frequency and the second collection frequency, and (ii) controls query access to the separate sample tables storing data collected at the first collection frequency and the second collection frequency, the separate sample tables further having the different levels of partitioning, wherein controlling the query access prevents performance of an ad hoc query on the first table for storing the data collected for the first fact and enables performance of an ad hoc query on the second table for storing the data collected for the second fact; and where the memory stores load logic configured to, when executed by the at least one processor, cause the computing system to: receive data for the plurality of facts; and store the received data received for the plurality of facts in the separate sample tables in accordance with the different levels of partitioning assigned to the separate sample tables based on the first collection frequency and the second collection frequency.

7. The computing system of claim 6 , where a given point type identified by the point identifier corresponds to a status and the data describes the status of the given point type.

8. The computing system of claim 6 , where a given point type identified by the point identifier corresponds to a relationship and the data is related to the given point type.

9. A computer-implemented method, comprising: identifying a plurality of facts comprising at least a first fact and a second fact, wherein each of the plurality of facts corresponds to a given attribute of a given point type, and data for the first fact is to be collected at a first collection frequency and data for the second fact is to be collected at a second collection frequency, wherein the first collection frequency is greater than the second collection frequency; determining the first collection frequency and the second collection frequency for the data to be collected for the plurality of facts; creating data structures defining separate sample tables, the separate sample tables comprising a first table for storing the data collected for the first fact and a second table for storing the data collected for the second fact, where the separate sample tables record a point identifier, the data, and a collection time for the data; selecting different levels of partitioning for the separate sample tables based, at least in part, on the first collection frequency and the second collection frequency of the data for the plurality of facts; control query access to the separate sample tables that store the data collected at the first collection frequency and the second collection frequency, and have the different levels of partitioning, wherein controlling the query access: prevents performance of an ad hoc query on the first table for storing the data collected for the first fact and enables performance of an ad hoc query on the second table for storing the data collected for the second fact; and storing subsequently received data in the sample tables according to the different levels of partitioning selected for the separate sample tables based on the different collection frequencies.

10. The computer-implemented method of claim 9 , further comprising deducing a valid time for the data based on the different collection frequencies.

11. The computer-implemented method of claim 9 , further comprising: assigning a unique fact identifier to the first fact and the second fact.

12. The computer-implemented method of claim 9 , where a given point type identified by the point identifier for the data corresponds to a relationship and the data is related to the given point type.

13. The computer-implemented method of claim 9 , where a given point type identified by the point identifier for the data corresponds to a status and the data describes the status of the given point type.